In typical semiconductor manufacturing processes, semiconductor wafers, or simply wafers, are advanced through a number of stations within what is referred to as a fab. At each location in this assembly line-like process, processing equipment or tools perform processing operations to modify the wafers. For example, one tool may add various layers onto the wafers (e.g., a deposition tool) while another may modify the layers (e.g., etching tools) to form a completed semiconductor product.
As they are moved through the assembly line, periodic quality checks are performed on the wafers. The quality checks typically include measuring widths of microscopic lines and film thicknesses on the wafer for aberrations. With many of the quality checks, the measurements can only be made after the wafers have undergone processing operations subsequent to those responsible for producing the aberrations. Furthermore, a period of time and a number of process steps typically pass between the introduction of the aberration and their detection. Thus, a number of processes may be performed on a wafer even after an aberration has been introduced. Similarly, a tool may continue processing wafers even after it has begun introducing aberrations. In either case, a number of wafers must be scrapped.
Conventional techniques are known for addressing some of these problems. Two examples include run-to-run control and fault detection.
Generally speaking, run-to-run control addresses process output drifts (i.e., drifts from process targets) by using data from outgoing and incoming wafers with modeling techniques to adjust process parameters. These drifts relate to slight changes in the way the tool produces output due to normal tool use. For example, with chemical mechanical polishing (CMP) processes, polishing pads used to reduce film thickness wear out over time. As a result, worn polishing pads inevitably require more time than new pads to produce a desired thickness. Run-to-run control may be used to address these types of problems by adjusting a process parameter such as polishing time to account for issues such as wear on a polishing pad.
Run-to-run control uses metrology data taken at one or more process steps to adjust process recipes (i.e., a set of predefined process parameters required to effectuate a processing outcome) on a run-to-run basis. A run may constitute one or more steps of a manufacturing process of a wafer. It may include a batch of wafer lots, a single lot or even a single wafer, depending on the particular needs and capabilities of the process step and the fab. In general, run-to-run control uses the data measured at each process or tool to keep wafer properties (e.g., film thickness, uniformity, etc.) close to their nominal values by making slight modifications or adjustments to the setpoints in each tool's recipe. In typical cases, data taken during or immediately after a process step on a particular tool is fed back to adjust the recipe for the following run. Similarly, data may be sent to the next tool to adjust downstream recipes. In this manner, run-to-run control may be used to address process output drifts.
While run-to-run control may be used to address process drifts, it is inadequate for situations where a tool is simply no longer capable of producing an acceptable product, regardless of adjustments made to the recipe setpoints. Similarly, run-to run control does not address situations where a wafer contains a flaw. These situations are termed tool or wafer property faults. A tool that has experienced a fault or failure condition causes the introduction of aberrations or flaws into the wafers. Similarly, a wafer property fault indicates a condition on the wafer that is beyond repair. A number of methods may be used to detect these conditions. For example, a significant drop in temperature from the temperature required to perform the given process operation may signify a fault. Another example of a fault condition may be a spike in a flow rate of a process material. In these instances, run-to-run controllers treat the fault as a drift and attempt to remedy the situation by adjusting the tool's recipe even though the adjustments simply are not capable of addressing the problem. Thus, instead of returning the tool to acceptable operating conditions, the tool continues to introduce aberrations in subsequent wafers or continues processing a flawed wafer thereby resulting in additional waste.
Fault detection, in contrast to run-to-run control, monitors process equipment parameters and wafer attributes to detect tool and wafer property failure or fault conditions. Fault detection systems collect process data and analyze the data for an abnormality or fault during the operation of the process equipment. If a fault is detected, the fault detection system may have various methods of reacting. For example, the system may notify an equipment operator or even terminate execution of process equipment.
While fault detection is adequate for dealing with tool or wafer property failure situations, it does nothing to address process drifts. Thus, until a tool or process fails, fault detection systems remain silent and allow the tools to drift from optimal operating conditions.
As such, it is apparent that a need exists for increasingly efficient techniques for processing wafers. More particularly, what is needed is a system that is capable of addressing both process drifts and fault conditions.